ASSESSMENT TEMPLATES

Start with the work.
Build a better assessment.

Practical tasks, scoring rubrics, and follow-up questions for hiring AI engineers. Choose a workflow, adapt the brief, and agree what evidence your team needs.

Choose what you need to evaluate.

Which template fits your role?

Choose by the work, not just the job title
What the person will doStart hereEvidence to examine
Ship a complete AI featureAI engineer assessmentCorrectness, evaluation cases, failure handling, and tradeoffs.
Build agents that take actionsAI agent assessmentTool contracts, permission boundaries, retries, and stopping rules.
Find and ground answers in documentsRAG assessmentRetrieval quality, citation support, abstention, and version handling.
Develop with coding assistantsAI-assisted coding assessmentPatch correctness, regression tests, and review of generated changes.
Own architecture and technical tradeoffsSystem design assessmentRequirements, data boundaries, operations, and capacity assumptions.

Evaluating the assessment process itself? Use the integrity pilot brief to test configured environments with consenting internal testers.

What makes a useful hiring assessment?

Give candidates a task connected to the role, make the allowed tools explicit, collect the work, and ask them to explain their choices. Review the evidence against criteria agreed in advance. These templates provide starting points; calibrate them for your role and candidate population.

For implementation examples, explore the Amber hiring case study and JupiterBrains hiring case study. Reported customer outcomes are separate from the illustrative exercises in this library.

PUT IT TO WORK

Start with the role you’re hiring for.

Bring a job description, a few must-have skills, and your hiring timeline. We’ll help you shape the evaluation.

Talk to us ↗